Practice Test 4 | Google Cloud Certified Professional Cloud Architect | Dumps | Mock Test

Question 46

You’re working for a gaming company that collects a huge amount of player telemetry data and game events.

The main task is to capture, transform and archive in real time millions of messages on system performance, for analysis on player behavior and for gaming purposes.

Data must be available very quickly. Therefore it was thought to use, also in order not to create overload, the information that the system already produces and that are in Json format.

The archival time series database service selected must allow queries to access at least 10 TB of historical data

How do you process the collected information in order to be used real-time and batch and which storage solution would you choose?

A. Cloud Dataflow and Cloud Bigtable
B. Cloud Dataproc and Cloud Storage
C. Cloud Functions and Cloud Spanner
D. Data Catalog and Cloud Datalab
E. Cloud Dataprep and Cloud Data Fusion

A is correct. Cloud Dataflow is the only product that can process streaming and batch data at the same time. In addition, there are ready to use Templates, useful for streaming data transformation. Look at this link for any further detail:

https://github.com/GoogleCloudPlatform/DataflowTemplates

Cloud Bigtable provides a massively scalable NoSQL database suitable for low-latency and high-throughput workloads.

B is wrong. Cloud Dataproc is a service for running Apache Spark and Apache Hadoop clusters. It is not completely serveless and has limited support for streaming data.

Cloud Storage is an object storage solution that allows worldwide storage and retrieval of any amount of data at any time. It is not a Database.

C is wrong. Cloud Functions is a serverless execution environment for building and connecting cloud services. You write simple, single-purpose functions that are attached to events released from your cloud infrastructure and services. Also, in this case, there is no direct support for streaming data. In any case, you have to write all your code.

Cloud Spanner is a powerful, mission-critical, scalable relational database service, built to support transactions, strong consistency, and high availability across regions and continents. It doesn’t have the required speed of Bigtable.

D is wrong. Data Catalog is a fully managed and scalable metadata management service that helps to discover, manage, and understand all their data in Google Cloud. So, it performs a completely different task. The same goes for Cloud Datalab which is a visual tool created to explore, analyze, transform, and visualize data already stored somewhere and build machine-learning models on Google Cloud Platform.

E is wrong. Cloud Dataprep is a tool for cleaning and preparing structured and unstructured data for analysis. Cloud Data Fusion is a fully managed, cloud-native data integration service that helps users efficiently build and manage ETL/ELT data pipelines. With a graphical interface and a broad open-source library of preconfigured connectors and transformations, Data Fusion shifts an organization’s focus away from code and integration to insights and action. The problem, even in this case, is that there is no direct support for streaming data.

For any further detail, please visit the following URLs:

https://cloud.google.com/dataflow/docs/

https://github.com/GoogleCloudPlatform/DataflowTemplates

https://cloud.google.com/bigtable/docs/